Question: How can I improve the accuracy of my AR/VR applications with high-quality training data?

SuperAnnotate is an all-purpose end-to-end enterprise platform for training, testing and deploying LLM, CV and NLP models. It can gather data from local and cloud storage systems, has a customizable interface and includes sophisticated AI, QA and project management tools. With a global marketplace of 400+ vetted annotation teams and support for many types of data, SuperAnnotate can help you get the best possible training data and then deploy your models to many different destinations.

Another good choice is Appen, which offers carefully prepared data for foundation models and other AI applications that enterprises need. Appen's service includes human feedback and human-AI collaboration, supports a broad range of data types, and offers a variety of deployment options. With more than 20,000 AI projects under its belt, Appen is a well-established partner for many big brands, and its service can be scaled up to gather, curate and fine-tune data for traditional machine learning and generative AI models.

For computer vision tasks, including predictive and generative models, Encord is a full-stack data development platform. It includes tools for ingesting data, cleaning it, curating it, automatically labeling it and evaluating model performance. Encord's service is designed to keep data flowing smoothly with integration tools and strong security, so you can focus on maintaining high-quality training data and improving model performance.